Scientific Understanding of Consciousness
Consciousness as an Emergent Property of Thalamocortical Activity

Decorrelated Neuronal Firing in Cortical Microcircuits

 

Science 29 January 2010: Vol. 327. no. 5965, pp. 584 - 587

Decorrelated Neuronal Firing in Cortical Microcircuits

Alexander S. Ecker,^1,2,3 Philipp Berens,^1,2,3 Georgios A. Keliris,¹ Matthias Bethge,^1,2 Nikos K. Logothetis,^1,4 Andreas S. Tolias^3,5,6

¹ Max Planck Institute for Biological Cybernetics, 72076 Tübingen, Germany.
² Centre for Integrative Neuroscience and Institute for Theoretical Physics, University of Tübingen, 72076 Tübingen, Germany.
³ Department of Neuroscience, Baylor College of Medicine, Houston, TX 77030, USA.
⁴ Division of Imaging Science and Biomedical Engineering, University of Manchester, Manchester M1 7HL, UK.
⁵ Michael E. DeBakey Veterans Affairs Medical Center, Houston, TX 77030, USA.
⁶ Department of Computational and Applied Mathematics, Rice University, Houston, TX 77005, USA.

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Correlated trial-to-trial variability in the activity of cortical neurons is thought to reflect the functional connectivity of the circuit. Many cortical areas are organized into functional columns, in which neurons are believed to be densely connected and to share common input. Numerous studies report a high degree of correlated variability between nearby cells. We developed chronically implanted multitetrode arrays offering unprecedented recording quality to reexamine this question in the primary visual cortex of awake macaques. We found that even nearby neurons with similar orientation tuning show virtually no correlated variability. Our findings suggest a refinement of current models of cortical microcircuit architecture and function: Either adjacent neurons share only a few percent of their inputs or, alternatively, their activity is actively decorrelated.

Our findings have implications for models of cortical circuit architecture. The current view on the generation of correlations in cortical circuits rests on two major assumptions: (i) nearby cortical neurons receive a substantial amount of common input (ii) such common input leads to correlations. In light of our data, at least one of these assumptions cannot be correct.

Based on measured spike count correlations, an influential modeling study inferred that, on average, nearby cells share up to 30% of their inputs. Under the same model, our data suggest that at most, 5% of the inputs are shared. Note that anatomical studies report ~10% common inputs for excitatory neurons. In addition, cortical excitatory connections may be very precisely structured to form many independent subunits. (highly differentiated)  In this case, most recorded pairs consist of neurons belonging to different subunits, and average correlations are very low.

Assumption (ii) has been challenged by recent network models in which a dynamic balance of excitatory and inhibitory fluctuations counteracts correlations induced by common inputs. This results in correlations that are positive on average but very low (~0.01), a prediction in good agreement with our data. To prevent small correlations from accumulating and dominating network activity, such a decorrelation mechanism might be a crucial prerequisite of hierarchical cortical processing.

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